Data Engineer

We have an immediate opportunity for an Entry to Mid-level Data Engineer to join our technology team. In this role, you will collaborate with other engineers, our internal product committee, and end-users to deliver high quality data solutions for large-scale property tax management. This position, and KE Andrews as a company, is geared towards individuals with a long-term outlook that want to turn a role into a career, not just work a job.

• Design, build, and maintain Python-based ETL pipelines to ingest, transform, and load data from a variety of sources.
• Write and optimize SQL-based ETL workflows and data transformations to support downstream analytics and reporting.
• Develop and manage data workflows within Databricks, including notebooks, jobs, and cluster configurations.
• Support and maintain data models and datasets consumed by Tableau, Alteryx, Hex and other BI tools.
• Monitor pipeline performance, troubleshoot data quality issues, and implement fixes as needed.
• Collaborate with analysts and business stakeholders to understand data needs and translate them into engineering solutions.
• Participate in requirements discussions and design sessions with senior engineers and product stakeholders.
• Occasionally serve as support lead, rotating through the team to handle production-related data requests.
• Document pipelines, data models, and processes to support team knowledge sharing.
• Collaborate with teammates during standups, demos, pull request reviews, sprint planning, and retrospectives.

• 0–5 years of experience in data engineering or a related role.
• Familiarity or hands-on experience with technologies such as:
• ETL & Transformation:
  Python, SQL
• Data Platform:
  Databricks, Snowflake, Synapse/Fabric
• Analytics & BI:
  Tableau, and other BI tools
• Strong problem-solving skills and attention to detail.
• Effective communicator who enjoys working in a collaborative team environment.
• A passion for continuous learning and growing as a data engineer.

• ETL & Pipelines:
  Python, SQL
• Data Platform:
  Databricks (notebooks, jobs, cluster management)
• Analytics & BI:
  Tableau, Hex.tech, Alteryx, additional BI tooling
• Additional Tools:
  Git Hub, Jira,

• 9/80 and 4.5/40 schedule options
• Hybrid work schedule
• Full health benefits
• 401(k) with 4% automatic contribution